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Adverse diagnostic events in hospitalised patients: a single-centre, retrospective cohort study
  1. Anuj K Dalal1,2,3,
  2. Savanna Plombon1,3,
  3. Kaitlyn Konieczny1,
  4. Daniel Motta-Calderon1,4,
  5. Maria Malik1,5,
  6. Alison Garber1,6,
  7. Alyssa Lam1,
  8. Nicholas Piniella1,
  9. Marie Leeson1,
  10. Pamela Garabedian1,3,
  11. Abhishek Goyal1,3,
  12. Stephanie Roulier1,3,
  13. Cathy Yoon1,
  14. Julie M Fiskio3,
  15. Kumiko O Schnock1,2,
  16. Ronen Rozenblum1,2,
  17. Jacqueline Griffin7,
  18. Jeffrey L Schnipper1,2,3,
  19. Stuart Lipsitz1,2,
  20. David W Bates1,2,3
  21. Patient Safety Learning Laboratory Adjudicator Group
      1. 1 Department of Medicine, Division of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
      2. 2 Harvard Medical School, Boston, Massachusetts, USA
      3. 3 Mass General Brigham, Boston, Massachusetts, USA
      4. 4 Vanderbilt University Medical Center, Nashville, Tennessee, USA
      5. 5 Dartmouth-Hitchcock Medical Center, Lebanon, Pennsylvania, USA
      6. 6 Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA
      7. 7 Department of Industrial Engineering, Northeastern University - Boston Campus, Boston, Massachusetts, USA
      1. Correspondence to Dr Anuj K Dalal; adalal1{at}bwh.harvard.edu

      Abstract

      Background Adverse event surveillance approaches underestimate the prevalence of harmful diagnostic errors (DEs) related to hospital care.

      Methods We conducted a single-centre, retrospective cohort study of a stratified sample of patients hospitalised on general medicine using four criteria: transfer to intensive care unit (ICU), death within 90 days, complex clinical events, and none of the aforementioned high-risk criteria. Cases in higher-risk subgroups were over-sampled in predefined percentages. Each case was reviewed by two adjudicators trained to judge the likelihood of DE using the Safer Dx instrument; characterise harm, preventability and severity; and identify associated process failures using the Diagnostic Error Evaluation and Research Taxonomy modified for acute care. Cases with discrepancies or uncertainty about DE or impact were reviewed by an expert panel. We used descriptive statistics to report population estimates of harmful, preventable and severely harmful DEs by demographic variables based on the weighted sample, and characteristics of harmful DEs. Multivariable models were used to adjust association of process failures with harmful DEs.

      Results Of 9147 eligible cases, 675 were randomly sampled within each subgroup: 100% of ICU transfers, 38.5% of deaths within 90 days, 7% of cases with complex clinical events and 2.4% of cases without high-risk criteria. Based on the weighted sample, the population estimates of harmful, preventable and severely harmful DEs were 7.2% (95% CI 4.66 to 9.80), 6.1% (95% CI 3.79 to 8.50) and 1.1% (95% CI 0.55 to 1.68), respectively. Harmful DEs were frequently characterised as delays (61.9%). Severely harmful DEs were frequent in high-risk cases (55.1%). In multivariable models, process failures in assessment, diagnostic testing, subspecialty consultation, patient experience, and history were significantly associated with harmful DEs.

      Conclusions We estimate that a harmful DE occurred in 1 of every 14 patients hospitalised on general medicine, the majority of which were preventable. Our findings underscore the need for novel approaches for adverse DE surveillance.

      • Diagnostic errors
      • Adverse events, epidemiology and detection
      • Patient safety
      • Hospital medicine
      • Information technology

      Data availability statement

      Data are available upon reasonable request.

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      Footnotes

      • X @tweet_akdMD, @drjschnip, @dbatessafety

      • Collaborators Patient Safety Learning Laboratory Adjudicator Group: David Lee MD; Daniel Palazuelos MD, MPH; Myrna Katalina Serna MD, MPH; Anne Kozak MS, PA-C; Khelsea O’Brien MS, PA-C; Shela Shah MD; Mohammed Wazir MD; Chadi Cortas MD, MD, MBA; Caroline Yang MD.

      • Contributors All authors contributed sufficiently to the conceptualisation (AKD, PG, RR, JG, JLS, SL, DWB), methodology (AKD, SP, DM-C, PG, RR, JG, JLS, SL, DWB); data curation (SP, KK, DM-C, AG, SR, MM, AL, NP, JMF); analysis (AKD, SP, KK, DM-C, MM, NP, CY, JMF, JLS, SL, DWB); project administration (AKD, SP, KK, DM-C, MM, AG, SR, AL, NP, ML); writing, editing and review of the manuscript (AKD, SP, KK, DM-C, AG, SR, MM, AG, AL, NP, ML, CY, JMF, PG, KOS, RR, JG, JLS, SL, DWB); and/or supervision and acquisition of funding (AKD, DWB).The guarantor (AKD) accepts full responsibility for the conduct of the study, analysis and access to data, decision to publish, and the finished work product.

      • Funding This study was funded by Agency for Healthcare Research and Quality (AHRQ) (R18 HS026613).

      • Competing interests None declared.

      • Provenance and peer review Not commissioned; externally peer reviewed.

      • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.